With the continuous development of internet technology, the concept of Web 3.0 has gradually emerged. Web 3.0 aims to build a more open, decentralized, user-owned data network ecosystem. However, the current development of Web 3.0 faces numerous challenges, such as user authentication, smart contract security, and data privacy protection. AI Agents, as a new type of intelligent entity, are expected to play an important role in Web 3.0, addressing these issues.

The potential of AI Agents in combination with Web3 is mainly reflected in the following three aspects:

1. Data provision and model training

The decentralized model of Web3 allows users to autonomously provide data, forming a data source for model training, and receive project benefits in the form of tokens. The more users there are, the greater the platform's profit, thereby attracting more data providers and further optimizing the model. This model is different from the centralized data model of Web2, presenting a positive feedback effect of 'stepping on the left foot with the right foot.' However, the development of AI is still in its early stages, and the user base of Web3 is relatively low, with the actual market effects still not significant.

2. Balancing information asymmetry

The transparency of blockchain brings a wealth of publicly available information, but the sheer volume of information is overwhelming and scattered, making it difficult for users to comprehensively and accurately obtain the information they need. AI Agents can integrate information from different blockchains, provide simplified analysis and risk assessment, and help users grasp market dynamics. By refining and analyzing data, AI Agents can effectively alleviate the information burden on users and provide them with more informed decision support.

3. Tokenization of AI Agents

Users can list and sell their self-built AI Agents, achieving the tokenization of AI Agents and thereby enhancing the richness of applications on the Web3 platform. This not only creates an incentive for users to design AI Agents but also helps to increase the token's value capture capability. In this model, AI Agents can be transferred, traded, or shared like NFTs, providing a more flexible usage and revenue model.